Song Zhiwei

Singapore Polytechnic, University of Science and Technology of China

Papers

Total Citations

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About

Song Zhiwei is a pioneering researcher in robotics and multi-agent systems, with a focus on humanoid locomotion, service robot localization, and collaborative decision-making. His most influential work, "Optimal energy gait planning for humanoid robot using geodesics" (2010, 7 citations), introduces a novel method that leverages geodesic theory to minimize kinetic energy during walking, modeling the center of gravity and single support phase with a 2D inverted pendulum—a foundational contribution to energy-efficient bipedal locomotion. In "A new sensor fusion framework to deal with false detections for low-cost service robot localization" (2013, 4 citations), he addresses a critical challenge in affordable robotics by developing a fusion technique that mitigates false detections from low-cost cameras, enhancing reliability in cluttered environments. Earlier, his work on "Layered decision-making and planning in ShaoLing team" (2002, 3 citations) advanced multi-agent coordination in real-time, adversarial domains like RoboCup soccer, enabling autonomous agents to act effectively both individually and as a team. Additionally, his "Kneed passive dynamic walker controller design employing a climbing learning algorithm" (2009, 2 citations) tackles the complex dynamics of passive walkers, allowing them to start from random states. With a career spanning over two decades, Song’s research bridges theoretical optimization and practical robotics, impacting fields from humanoid design to affordable service robots.